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TRV-2026-0173Certified recordPeer-reviewed

A Triple-Intelligence Framework for Sustainable AI-Driven Workforce Analytics: Integrating Artificial Intelligence, Human Judgment, and Organizational Governance

The use of Artificial Intelligence (AI) within workforce analytics represents a paradigm shift in how organizations make decisions regarding their employees. While AI-enabled workforce analytics can enable proactive and predictive decision-making, the literature identifies multiple substantive risks associated with the use of AI in workforce analytics, namely: algorithmic opacity, automation bias, proxy-based discrimination, and employee surveillance. This literature gap was addressed through developing and vali…

Labor · The Trace — both readings · certified 2026-07-13 · v1 · article view · machine-readable

Current reading — gain

AI use in workforce analytics enables proactive and predictive decision-making about employees.

Current reading — problem

AI use in workforce analytics introduces substantive risks including algorithmic opacity, automation bias, proxy-based discrimination, and employee surveillance.

What this doesn’t fix

Framework development and validation is based on a systematic literature review from 2017-2025 and scoped to four high-risk workforce decision domains, not organization-wide empirical deployment.

Evidence

Reader signal

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Truvace Impact Record TRV-2026-0173, v1: “A Triple-Intelligence Framework for Sustainable AI-Driven Workforce Analytics: Integrating Artificial Intelligence, Human Judgment, and Organizational Governance.” Truvace, 2026-07-13. /record/TRV-2026-0173 (accessed at citation time). sha256 c03c7ca120e7ead6…

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